Recent reports suggest that 10 to 30% of severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) infected patients are asymptomatic and that viral shedding may occur before symptom onset. Therefore, there is an urgent need to increase diagnostic testing capabilities to prevent disease spread. We developed P-BEST, a method for Pooling-Based Efficient SARS-CoV-2 Testing, which identifies all positive subjects within a set of samples using a single round of testing. Each sample is assigned into multiple pools using a combinatorial pooling strategy based on compressed sensing. We pooled sets of 384 samples into 48 pools, providing both an eightfold increase in testing efficiency and an eightfold reduction in test costs, while identifying up to five positive carriers. We then used P-BEST to screen 1115 health care workers using 144 tests. P- BEST provides an efficient and easy-to-implement solution for increasing testing capacity that can be easily integrated into diagnostic laboratories.

最近的报告表明，10% 至 30% 的严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 感染患者无症状，并且病毒排毒可能在症状出现之前发生。因此，迫切需要提高诊断检测能力以防止疾病传播。我们开发了 P-BEST，一种基于池的高效 SARS-CoV-2 测试方法，该方法使用单轮测试即可识别一组样本中的所有阳性受试者。使用基于压缩感知的组合池策略将每个样本分配到多个池中。我们将 384 个样本汇集到 48 个池中，使检测效率提高了八倍，检测成本降低了八倍，同时识别出最多 5 个阳性携带者。然后，我们使用 P-BEST 通过 144 项测试对 1115 名医护人员进行了筛查。P-BEST 提供了一种高效且易于实施的解决方案，用于提高测试能力，并且可以轻松集成到诊断实验室中。